Depression and anxiety symptoms: onset, developmental course and risk factors during early childhood
Bibliographic record
Abstract
BACKGROUND: Depressive and anxiety disorders are among the top ten leading causes of disabilities. We know little, however, about the onset, developmental course and early risk factors for depressive and anxiety symptoms (DAS). OBJECTIVE: Model the developmental trajectories of DAS during early childhood and to identify risk factors for atypically high DAS. METHOD: Group-based developmental trajectories of DAS conditional on risk factors were estimated from annual maternal ratings (1(1/2) to 5 years) in a large population sample (n = 1759). RESULTS: DAS increased substantially in two of the three distinct trajectory groups identified: High-Rising (14.7%); Moderate-Rising (55.4%); and Low (29.9%). Two factors distinguished the High-Rising group from the other two: Difficult temperament at 5 months (High-Rising vs Moderate-Rising: OR = 1.32; 95% CI = 1.13-1.55; High-Rising vs Low: OR = 1.31, CI = 1.12-1.54) and maternal lifetime major depression (High-Rising vs Moderate-Rising: OR = 1.10; CI = 1.01-1.20; High-Rising vs Low: OR = 1.19; CI = 1.08-1.31). Two factors distinguished the High-Rising group from the Low group: High family dysfunction (OR = 1.24; CI = 1.03-1.5) and Low parental self-efficacy (OR = .71; CI = .54-.94). CONCLUSIONS: DAS tend to increase in frequency over the first 5 years of life. Atypically high level can be predicted from mother and child characteristics present before 6 months of age. Preventive interventions should be experimented with at risk infants and parents.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".